There are many categories available on Steemit under which you can publish a post. Consistently in the top 10 categories is Life. Being such a popular category to post in, I felt it was important to document the data for this category in 2017
Categories are set by the 'Tags' you select when publishing a post. The first 'Tag' that you select is the Category the post will be recorded in. Once a post has been published on the Steemit platform, tags can be changed but the category will no change.
The aim of this analysis is to
Get an overview and document of the posts made to Life in 2017
Look at the growth of this category over 2017
Look at the earnings of this category during 2017
Look at top authors of this category
The data and the query
I have connected to the Steemsql database held and managed by using Microsofts Power BI
The SQL query used for this exploration is
Select *
FROM comments (NOLOCK)
where
( created >= CONVERT(datetime,'01/01/2017')
AND created< CONVERT(datetime,'01/01/2018')) and
Depth = 0
And category in ('life')
This query will pull all of the Posts made during 2017 in the category life. It will ignore any comments and will also ignore tags. Just to point out, the first tag that is selected on a post is the category in which a post is recorded.
After this I carried out further transformations on the data using M. First with this piece of code I removed any columns I did not want
= Table.SelectColumns(Source,{"author", "title", "body", "created", "children", "total_payout_value",
"net_votes", "pending_payout_value", "total_pending_payout_value"})
Then with this piece of code I changed the data type on the date field
= Table.TransformColumnTypes(#"Removed Other Columns",{{"created", type date}})
After this I loaded the data into the model and proceeded to model the data using DAX calculations.
The Analysis
In 2017 190K posts were created in the LIFE category by 29.83K authors. These posts netted 4018K votes and 807K comments and also generated a total SBD pay-out value of 842.68K.
The average number of monthly posts to Life is 15,874 and the median is 19,701. From May to July there was a steady increase in the number of posts per month. This then declined slightly in September and October, increasing again in Nov and Dec.
The visualisation above look at the SBD pay-outs. The bar chart shows the pay-outs over time. We can also see that 24% of posts earn between $1 and $50. This is the same as the Blog tag. Less than 2% of posts earned over $50. The balance of posts earned less than $1. The table on the right shows the top preforming posts in Life for 2017.
Let’s take a look at some averages
29.83K authors produced on average 6.39 posts each to the life category. The total of these 6.39 posts earned SBD 28.25 with the average post earning 4.42 SBD. On average each post received 4.24 comments and 21.09 votes. The average vote value on posts in the Life category was 0.21 SBD
For comparison the averages on the BLOG category are shown below
We can also view these averages over the year of 2017, we can see some peaks in payments from May to June with a decline till December where we can see another rise is all line except the average number of posts per author.
If we view the same information over months instead of days
We can see clearer now that the average SBD per post peaked in May and June, and then decreased again until another rise in December. It is also clear to see that the average number of comments left on a post also peaked in June and decreased from then with a small increase again in December.
Having a look at the authors that posted to the LIFE category, first I have sorted the data by the average number of comments per post. Comments are an awesome reflection on engagement within the post.
I then sorted the data by the average number of votes per post
And finally I have sorted the data by the total SBD pay out value on posts to cryptocurrency by author
The following cluster chart shows the Number of comments against the Post SBD pay out.
Conclusion
The Life tag/category on steemit is a busy and competitive category
We can see clearly that posts on average in the LIFE category tend to do better in terms of votes, payouts and comments than posts made in the BLOG category. However the overall trends remain the same.
You can find a full analysis of the BLOG category here
https://utopian.io/utopian-io/@paulag/steemit-2017-round-up-analyzing-the-blog-category
You can find a full analysis of the cryptocurrency category here
https://steemit.com/utopian-io/@paulag/steemit-2017-round-up-analyzing-the-cryptocurrency-tag
On saying that, this analysis does not take into consideration the quality of the post, however I do class comments as a good indicator of engagement. I am hopeful that the more quality the post, the more comments.
I am part of a Blockchain Business Intelligence community. We all post under the tag #BlockchainBI. If you have an analysis you would like carried out on Steemit or Blockchain data, please do contact me or any of the#BlockchainBI team and we will do our best to help you...
You can find #BlockchainBI on discord https://discordapp.com/invite/JN7Yv7j
Posted on Utopian.io - Rewarding Open Source Contributors